Sexual violence in the discourse of digital citizens: Strengthening the concept of digital citizenship as online civic engagement

B. Mulyono
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Abstract

Cases of sexual violence frequently exposed on social media have sparked intense discussions among digital citizens. This phenomenon has given rise to new patterns of participation in the digital public sphere, indicating progress in efficiently and effectively expressing public aspirations through online civic engagement. Thus, online citizen engagement further strengthens the concept of digital citizenship as an active participation form in the digital world. In this study, the topic modeling method is utilized as a machine learning approach with statistical methods to identify topics within large, unstructured document collections. The applied topic modeling method is Latent Dirichlet Allocation (LDA), using data collected from Twitter through crawling big data using the Twitter API. The results of this research reveal the discourse on sexual violence discussed by citizens with seven topics, namely: 1) Indonesia's sexual violence emergency; 2) Support for the enactment of the Draft Law on the Prevention of Sexual Violence, opposing parties against the Draft Law on the Prevention of Sexual Violence; 3) Pros and cons of Minister of Education and Culture and Research and Technology Regulation No. 30 of 2021 concerning the Prevention and Handling of Sexual Violence in Higher Education; 4) Sexual violence as sadistic behavior; 5) Sexual violence on campuses and in Islamic boarding schools; 6) Support for Minister of Education and Culture and Research and Technology Regulation No. 30 of 2021 for the prevention and handling of sexual violence on campuses; and 7) Stop sexual violence against children and women. From the analysis of the topic modeling results, it is evident that with a good understanding of citizen engagement facilitated by technology, the younger generation can develop digital citizenship in the practice of online civic engagement.
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数位公民话语中的性暴力:强化数位公民作为线上公民参与的概念
社交媒体上频繁曝光的性暴力案件引发了数字公民的激烈讨论。这一现象催生了数字公共领域的新参与模式,表明在通过在线公民参与高效和有效地表达公众愿望方面取得了进展。因此,在线公民参与进一步强化了数字公民作为数字世界积极参与形式的概念。在本研究中,主题建模方法被用作带有统计方法的机器学习方法,以识别大型非结构化文档集合中的主题。应用的主题建模方法是Latent Dirichlet Allocation (LDA),使用使用Twitter API抓取大数据从Twitter收集的数据。本研究的结果揭示了公民讨论性暴力的七个主题,即:1)印度尼西亚的性暴力紧急情况;2)支持制定《防止性暴力法草案》,反对《防止性暴力法草案》的各方;3)教育、文化、研究和技术部长关于预防和处理高等教育中的性暴力的2021年第30号条例的利弊;4)性暴力作为施虐行为;5)校园和伊斯兰寄宿学校的性暴力;6)支持教育文化和研究技术部长关于预防和处理校园性暴力的2021年第30号条例;7)制止针对儿童和妇女的性暴力。从主题建模结果的分析可以看出,在技术的推动下,年轻一代对公民参与有了很好的理解,就可以在网络公民参与的实践中发展数字公民。
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发文量
20
审稿时长
12 weeks
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